Mono-camera based vehicle localization using lidar intensity map for automated driving

This paper reports an image-based localization for automated vehicle. The proposed method utilizes a mono-camera and an inertial measurement unit to estimate the vehicle pose. Self-localization is implemented by a map matching technique between the reference digital map and sensor observations. In g...

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Veröffentlicht in:Artificial life and robotics 2019-06, Vol.24 (2), p.147-154
Hauptverfasser: Yoneda, Keisuke, Yanase, Ryo, Aldibaja, Mohammad, Suganuma, Naoki, Sato, Kei
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container_end_page 154
container_issue 2
container_start_page 147
container_title Artificial life and robotics
container_volume 24
creator Yoneda, Keisuke
Yanase, Ryo
Aldibaja, Mohammad
Suganuma, Naoki
Sato, Kei
description This paper reports an image-based localization for automated vehicle. The proposed method utilizes a mono-camera and an inertial measurement unit to estimate the vehicle pose. Self-localization is implemented by a map matching technique between the reference digital map and sensor observations. In general, the same types of sensors are used for map data and observations. However, this study is focused on the mono-camera based method using Lidar-based map for the purpose of a low-cost implementation. Image template matching is applied to provide a correlation distribution between the captured image and the predefined orthogonal map. A probability of the vehicle pose is then updated using the obtained correlation. The experiments were carried out for real driving data on an urban road. The results have verified that the proposed method estimates the vehicle position in 0.11[m] positioning errors on real-time.
doi_str_mv 10.1007/s10015-018-0502-6
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subjects Artificial Intelligence
Automation
Cameras
Computation by Abstract Devices
Computer Science
Control
Digital mapping
Inertial platforms
Lidar
Localization
Mechatronics
Original Article
Robotics
Template matching
title Mono-camera based vehicle localization using lidar intensity map for automated driving
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